As well known to those skilled in the art, an identity authentication system is used to restrict an access to a certain region or building, which needs security, to only previously registered persons. Among identity authentication systems, a smart card system is widely used, wherein various personal information of a user and PIN number for gaining an access to a certain building are stored in a smart card so that the access is given to the user only when the personal information and PIN number in the card are matched to those previously registered. However, the smart card system has a disadvantage in that a surreptitious use, counterfeiting and altering of the card by another person are relatively easy.
In recent days, interest is directed to a technological field of biometric identification using unique biometric information of a user such as a retina, iris, fingerprint, signature, voice or face for identity authentication, because of its superior security. Since security is a main concern of society, users require more reliable security systems. Thus, a security system using biometric identification shows significant increase in use in spite of its high establishment cost.
A conventional biometric information authentication system using the fingerprint, retina, iris, signature or etc. has a problem of causing inconvenience to a user upon entering biometric information, wherein the system forces the user to perform a certain behavior such as personally entering fingerprint information in a fingerprint recognition device or placing eyes very close to a iris recognition device. When face information among above biometric information is used, inconvenience or discomfort that the user experiences upon entering biometric information is much reduced, which is advantageous. Therefore, researches and studies into identity authentication technology using face identification have been actively conducted.
The researches and studies into the face identification can be conventionally classified into a holistic approach and an analytic approach.
The holistic approach represents a universe characteristic of face image domain by using a set of orthonormal basis vectors. One now widely used among the basis vectors is an eigenface. The eigenface is derived from the covariance analysis of the face image population. If two faces are sufficiently identical to each other in an eigenface feature space, they are regarded as the same. For example, a template matching-based face recognition system employs such holistic approach. The holistic approach considers all parts of a pattern, uses information of a whole image, thereby causing a problem of slow data processing.
The analytic approach extracts such facial attributes as nose and eyes from the face image and uses the invariance of geometric properties among the face landmark features, to thereby recognize the features of a face. This approach requires high recognition speed and low-memory, while the selection and extraction of features are difficult.
Recently, among the researches and studies into the face identification, a research and study using SVMs (Support Vector Machines) capable of performing a fine classification function has been actively conducted. The face identification usually applies the SVMs to information of whole face image, whereby the SVMs has to store SVs (Support Vectors) of high dimensions in order to store an OSH (Optimal Separating Hyperplane). This causes a problem in the SVMs themselves, that a large memory is required. Therefore, the face identification has a problem that it is hard to use in restricted environments, such as those with a limited memory and capability of calculation.